The "red herring" after 20 years: ageing and health care expenditures

Implications for household health expenditure in China's ageing population: based on Red Herring hypothesis

The rising healthcare costs due to population aging present a complex issue, with debate centering on whether these costs are driven by aging or end-of-life care. This study examines healthcare expenditures in Chinese households using data from the 2005 and 2018 Chinese Longitudinal Healthy Longevity Survey. By applying the Heckman select model and a two-part model, the research innovatively includes time to death, income, social security and health level in the benchmark regression in order to validate the recent some new Red Herring hypothesis. The findings show that time to death is the primary determinant of healthcare expenditures, while the effect of aging is minimal. Income, social security, and health status also significantly influence health expenditure, but they do not function as Red Herring variables.

A Case Management Approach in Stroke Care: A Mixed-Methods Acceptance Analysis From the Perspective of the Medical Profession

PURPOSE OF STUDY

In terms of continuous and coordinated health care, cross-sectoral care structures are crucial. However, the German health care system is characterized by fragmentation of medical services and responsibilities. This fragmentation leads to multiple interfaces frequently causing loss of information, effectiveness, and quality. The concept of case management has the potential to improve cooperation between sectors and health care providers. Hence, a case management intervention for patients with stroke was evaluated with an acceptance analysis on the physicians' willingness to cooperate with stroke managers and their assessment of the potential of case management for the health care of patients with stroke.

PRIMARY PRACTICE SETTINGS

Primary practice settings included physicians working in the hospital, rehabilitation, and outpatient sectors who had actual or potential contact with a stroke case manager within the project region of East Westphalia-Lippe.

METHODOLOGY AND SAMPLE

The analysis was conducted using a mixed-methods approach. Expert interviews were conducted in 2020. Afterward a questionnaire was developed, which was then distributed to physicians in 2021. Both the interviews and the questionnaire included questions on conceptual knowledge and concrete expectations prior of the project, on experiences during the project and on recommendations and physicians' assessment of future organization in health care to classify and describe the acceptance.

RESULTS

Nine interviews were conducted and 23 questionnaires were completed. Only slightly more than 50% of the physicians had prior knowledge of the case management approach. Overall, ambiguous results concerning the acceptance of case managers were revealed. Additional personal assistance for patients with stroke was seen as beneficial at the same time critical perspectives regarding further fragmentation of health care and overlapping of competences with existing professional groups or forms of health care were collected. General practitioners in particular were critical of the case management approach.

IMPLICATIONS FOR CASE MANAGEMENT PRACTICE

From the physicians' point of view, at least two changes are necessary for the project approach to be integrated into standard care. First, the target group should be adapted according to the case management approach. Second, the delegation of tasks and responsibilities to case managers should be revised. The sectoral difference in the acceptance of case managers by physicians indicates that active cooperation and communication in everyday work has direct impact on the acceptance of a new occupational profession. Physician acceptance has a significant impact on the implementation of new treatment modalities and thus influences the overall quality of health care.

End-of-life expenditure on health care for the older population: a scoping review

BACKGROUND

The existing evidence shows that the pattern of health expenditure differs considerably between people at the end-of-life and people in other periods of their lives. The awareness of these differences, combined with a detailed analysis of future mortality rates is one of the key pieces of information needed for health spending prognoses. The general objective of this review was to identify and map the existing empirical evidence on end-of-life expenditure related to health care for the older population.

METHODS

To achieve the objective of the study a systematic scoping review was performed. There were 61 studies included in the analysis. The project has been registered through the Open Science Framework.

RESULTS

The included studies cover different kinds of expenditure in terms of payers, providers and types of services, although most of them include analyses of hospital spending and nearly 60% of analyses were conducted for insurance expenditure. The studies provide very different results, which are difficult to compare. However, all of the studies analyzing expenditure by survivorship status indicate that expenditure on decedents is higher than on survivors. Many studies indicate a strong relationship between health expenditure and proximity to death and indicate that proximity to death is a more important determinant of health expenditure than age per se. Drawing conclusions on the relationship between end-of-life expenditure and socio-economic status would be possible only by placing the analysis in a broader context, including the rules of a health system's organization and financing. This review showed that a lot of studies are focused on limited types of care, settings, and payers, showing only a partial picture of health and social care systems in the context of end-of-life expenditure for the older population.

CONCLUSION

The results of studies on end-of-life expenditure for the older population conducted so far are largely inconsistent. The review showed a great variety of problems appearing in the area of end-of-life expenditure analysis, related to methodology, data availability, and the comparability of results. Further research is needed to improve the methods of analyses, as well as to develop some analysis standards to enhance research quality and comparability.

What drives health care spending in Switzerland? Findings from a decomposition by disease, health service, sex, and age

BACKGROUND

High and increasing spending dominates the public discussion on healthcare in Switzerland. However, the drivers of the spending increase are poorly understood. This study decomposes health care spending by diseases and other perspectives and estimates the contribution of single cost drivers to overall healthcare spending growth in Switzerland between 2012 and 2017.

METHODS

We decompose total healthcare spending according to National Health Accounts by 48 major diseases, injuries, and other conditions, 20 health services, 21 age groups, and sex of patients. This decomposition is based on micro-data from a multitude of data sources such as the hospital inpatient registry, health and accident insurance claims data, and population surveys. We identify the contribution of four main drivers of spending: population growth, change in population structure (age/sex distribution), changes in disease prevalence, and changes in spending per prevalent patient.

RESULTS

Mental disorders were the most expensive major disease group in both 2012 and 2017, followed by musculoskeletal disorders and neurological disorders. Total health care spending increased by 19.7% between 2012 and 2017. An increase in spending per prevalent patient was the most important spending driver (43.5% of total increase), followed by changes in population size (29.8%), in population structure (14.5%), and in disease prevalence (12.2%).

CONCLUSIONS

A large part of the recent health care spending growth in Switzerland was associated with increases in spending per patient. This may indicate an increase in the treatment intensity. Future research should show if the spending increases were cost-effective.

A study on the sustainability assessment of China's basic medical insurance fund under the background of population aging-evidence from Shanghai

Objective

As China's population aging process accelerates, the expenditure of China's basic medical insurance fund for employees may increase significantly, which may threaten the sustainability of China's basic medical insurance fund for employees. This paper aims to forecast the future development of China's basic medical insurance fund for employees in the context of the increasingly severe aging of the population.

Methods

This paper taking an empirical study from Shanghai as an example, constructs an actuarial model to analyze the impact of changes in the growth rate of per capita medical expenses due to non-demographic factors and in the population structure on the sustainability of the basic medical insurance fund for employees.

Results

Shanghai basic medical insurance fund for employees can achieve the goal of sustainable operation in 2021-2035, with a cumulative balance of 402.150-817.751 billion yuan in 2035. The lower the growth rate of per capita medical expenses brought about by non-demographic factors, the better the sustainable operation of the fund.

Conclusion

Shanghai basic medical insurance fund for employees can operate sustainably in the next 15 years, which can further reduce the contribution burden of enterprises, which lays the foundation for improving the basic medical insurance treatment for employees.

From population numbers to population needs: Incorporating epidemiological change into health service planning in Australia

BACKGROUND

In the face of rapidly ageing populations and increasing costs of health care provision, questions continue to be raised about the long-term sustainability of publicly funded health care programmes around the world. But despite increasing evidence of dynamic changes in epidemiology, most official health service planning models continue to rely on the implicit assumption that age-specific requirements for services (and by implication age-specific needs for care) will remain constant across future years ('constant-use models').

OBJECTIVES

In this paper, we discuss the advantage of dynamic 'changing needs' planning models, compared to 'constant-use' planning models, and consider a framework that integrates population needs directly into health service planning. Using Australian survey data, we empirically illustrate the difference between static health service planning approaches to dynamic needs-driven planning models.

METHODS

We use data from the Household, Income and Labour Dynamics Survey in Australia (HILDA) to explore trends in health needs from 2001 to 2020. We subsequently simulate a 'changing-needs' planning model where changes in health needs by birth-cohorts are incorporated into official government estimates from the Australian Intergenerational Reports (IGR) to understand the potential impact on future health care requirements.

RESULTS

Our results show that healthy ageing trends are being observed for successive birth-cohorts with these trends greatest in older age groups, the age groups for which health care expenditures are largest. Adjusting for these changes in needs using Australian data leads to reductions in the expenditures required for future years ranging from 1.5 (2.50%) to 3 billion (5.25%.%) 2019 AUD.

CONCLUSION

We conclude that 'constant-use' planning models based on the expected future numbers of people in different age groups applied to current levels of service use by age groups without any consideration given to changing age-specific needs for health care lead to inefficient resource planning.

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes

BACKGROUND

Although pharmaceutical expenditures have been rising for decades, the question of their drivers remains unclear, and long-term projections of pharmaceutical spending are still scarce. We use a Markov approach considering different cost-risk groups to show the possible range of future drug spending in Germany and illustrate the influence of various determinants on pharmaceutical expenditure.

METHODS

We compute different medium and long-term projections of pharmaceutical expenditure in Germany up to 2060 and compare extrapolations with constant shares, time-to-death scenarios, and Markov modeling based on transition probabilities. Our modeling is based on data from a large statutory sickness fund covering around four million insureds. We divide the population into six risk groups according to their share of total pharmaceutical expenditures, determine their cost growth rates, survival and transition probabilities, and compute different scenarios related to changes in life expectancy or spending trends in different cost-risk groups.

RESULTS

If the spending trends in the high-cost groups continue, per-capita expenditure will increase by over 40% until 2040. By 2060, pharmaceutical expenditures could more than double, even if these groups would not benefit from rising life expectancy. By contrast, the isolated effect of demographic change would "only" lead to a long-term increase of around 15%.

CONCLUSION

The long-term development of pharmaceutical spending in Germany will depend mainly on future expenditure and life expectancy trends of particularly high-cost patients. Thus, appropriate pricing of new expensive pharmaceuticals is essential for the sustainability of the German healthcare system.

Formal health care costs among older people in Ireland: methods and estimates using The Irish Longitudinal Study on Ageing (TILDA)

Background: Reliable data on health care costs in Ireland are essential to support planning and evaluation of services. New unit costs and high-quality utilisation data offer the opportunity to estimate individual-level costs for research and policy. Methods: Our main dataset was The Irish Longitudinal Study on Ageing (TILDA). We used participant interviews with those aged 55+ years in Wave 5 (2018) and all end-of-life interviews (EOLI) to February 2020. We weighted observations by age, sex and last year of life at the population level. We estimated total formal health care costs by combining reported usage in TILDA with unit costs (non-acute care) and public payer reimbursement data (acute hospital admissions, medications). All costs were adjusted for inflation to 2022, the year of analysis. We examined distribution of estimates across the population, and the composition of costs across categories of care, using descriptive statistics. We identified factors associated with total costs using generalised linear models. Results: There were 5,105 Wave 5 observations, equivalent at the population level to 1,207,660 people aged 55+ years and not in the last year of life, and 763 EOLI observations, equivalent to 28,466 people aged 55+ years in the last year of life. Mean formal health care costs in the weighted sample were EUR 8,053; EUR 6,624 not in the last year of life and EUR 68,654 in the last year of life. Overall, 90% of health care costs were accounted for by 20% of users. Multiple functional limitations and proximity to death were the largest predictors of costs. Other factors that were associated with outcome included educational attainment, entitlements to subsidised care and serious chronic diseases. Conclusions: Understanding the patterns of costs, and the factors associated with very high costs for some individuals, can inform efforts to improve patient experiences and optimise resource allocation.

Utilization and out-of-pocket expenses of primary care among the multimorbid elderly in China: A two-part model with nationally representative data

Background

Multimorbidity has become an essential public health issue that threatens human health and leads to an increased disease burden. Primary care is the prevention and management of multimorbidity by providing continuous, comprehensive patient-centered services. Therefore, the study aimed to investigate the determinants of primary care utilization and out-of-pocket expenses (OOPE) among multimorbid elderly to promote rational utilization of primary care and reduce avoidable economic burdens.

Methods

The study used data from CHARLS 2015 and 2018, which included a total of 4,384 multimorbid elderly aged 60 and above. Guided by Grossman theory, determinants such as education, gender, marriage, household economy, and so on were included in this study. A two-part model was applied to evaluate primary care utilization and OOPE intensity in multimorbid populations. And the robustness testing was performed to verify research results.

Results

Primary care visits rate and OOPE indicated a decline from 2015 to 2018. Concerning primary outpatient care, the elderly who were female (OR = 1.51, P < 0.001), married (OR = 1.24, P < 0.05), living in rural areas (OR = 1.77, P < 0.001) and with poor self-rated health (OR = 2.23, P < 0.001) had a significantly higher probability of outpatient utilization, whereas those with middle school education (OR = 0.61, P < 0.001) and better household economy (OR = 0.96, P < 0.001) had a significantly less likelihood of using outpatient care. Rural patients (β = -0.72, P < 0.05) may have lower OOPE, while those with better household economy (β = 0.29, P < 0.05; β = 0.58, P < 0.05) and poor self-rated health (β = 0.62, P < 0.001) occurred higher OOPE. Regarding primary inpatient care, adults who were living in rural areas (OR = 1.48, P < 0.001), covered by Urban Employee Basic Medical Insurance (UEBMI) or Urban Rural Basic Medical Insurance (URBMI) (OR = 2.46, P < 0.001; OR = 1.81, P < 0.001) and with poor self-rated health (OR = 2.30, P < 0.001) had a significantly higher probability of using inpatient care, whereas individuals who were female (OR = 0.74, P < 0.001), with middle school education (OR = 0.40, P < 0.001) and better household economy (OR = 0.04, P < 0.001) had a significantly lower tendency to use inpatient care. Significantly, more OOPE occurred by individuals who were women (β = 0.18, P < 0.05) and with better household economy (β = 0.40, P < 0.001; β = 0.62, P < 0.001), whereas those who were covered by URBMI (β = -0.25, P < 0.05) and satisfied with their health (β = -0.21, P < 0.05) had less OOPE.

Conclusion

To prompt primary care visits and reduce economic burden among subgroups, more policy support is in need, such as tilting professional medical staff and funding to rural areas, enhancing awareness of disease prevention among vulnerable groups and so on.

Ageing and health care expenditures: the importance of age per se, steepening of the individual-level expenditure curve, and the role of morbidity

The demographic change towards a larger proportion of older individuals challenges universal health care systems in sustaining high-quality care and universal coverage without budget expansions. To build valuable predictions of the economic burden from population ageing, it is crucial to understand the determinants of individual-level health care expenditures. Often, the focus has been on the relative importance of an individual's age and time to death, while only a few newer studies highlight that individual-level health care expenditures are increasing faster for the elderly-i.e., creating a steepening of the individual-level health care expenditure curve over time. Applying individual-level administrative data for the entire Danish population, our study is the first to use a single data set to examine whether age, time to death, and a steepening of the individual-level health care expenditure curve all contributed to individual-level health care expenditures over a 12 year observation period (2006-2018). We find that individual-level expenditures are associated with an individual's age, an individual's time to death, and a steepening of the expenditure curve, with the steepening driven by individuals above age 75. We observe heterogeneity in the extent and age distribution of steepening across disease groups. The threefold combination of an ageing population, the correlation between expenditures and age per se, and a steepening of the expenditure curve make establishing financially sustainable universal health care systems increasingly difficult. To mitigate budgetary pressure, policy-makers should stimulate cost-effective medical advances and health care utilization in the treatment of elderly. Moreover, steepening scenarios should be added to future health care expenditure forecasts.

Predicting mortality in The Irish Longitudinal Study on Ageing (TILDA): development of a four-year index and comparison with international measures

Objectives

We aimed to replicate existing international (US and UK) mortality indices using Irish data. We developed and validated a four-year mortality index for adults aged 50 + in Ireland and compared performance with these international indices. We then extended this model by including additional predictors (self-report and healthcare utilization) and compared its performance to our replication model.

Methods

Eight thousand one hundred seventy-four participants in The Irish Longitudinal Study on Ageing were split for development (n = 4,121) and validation (n = 4,053). Six baseline predictor categories were examined (67 variables total): demographics; cardiovascular-related illness; non-cardiovascular illness; health and lifestyle variables; functional variables; self-report (wellbeing and social connectedness) and healthcare utilization. We identified variables independently associated with four-year mortality in the development cohort and attached these variables a weight according to strength of association. We summed the weights to calculate a single index score for each participant and evaluated predicted accuracy in the validation cohort.

Results

Our final 14-predictor (extended) model assigned risk points for: male (1pt); age (65–69: 2pts; 70–74: 4 pts; 75–79: 4pts; 80–84: 6pts; 85 + : 7pts); heart attack (1pt); cancer (3pts); smoked past age 30 (2pts); difficulty walking 100 m (2pts); difficulty using the toilet (3pts); difficulty lifting 10lbs (1pts); poor self-reported health (1pt); and hospital admission in previous year (1pt). Index discrimination was strong (ROC area = 0.78).

Discussion

Our index is predictive of four-year mortality in community-dwelling older Irish adults. Comparisons with the international indices show that our 12-predictor (replication) model performed well and suggests that generalisability is high. Our 14-predictor (extended) model showed modest improvements compared to the 12-predictor model.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03196-z.

Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure

This study measures the increment of health care expenditure (HCE) that can be attributed to technological progress and change in medical practice by using a residual approach and microdata. We examine repeated cross-sections of individuals experiencing an initial health shock at different point in time over a 10-year window and capture the impact of unobservable technology and medical practice to which they are exposed after allowing for differences in health and socioeconomic characteristics. We decompose the residual increment in the part that is due to the effect of delaying time to death, that is, individuals surviving longer after a health shock and thus contributing longer to the demand of care, and the part that is due to increasing intensity of resource use, that is, the basket of services becoming more expensive to allow for the cost of innovation. We use data from the Danish National Health System that offers universal coverage and is free of charge at the point of access. We find that technological progress and change in medical practice can explain about 60% of the increment of HCE, in line with macroeconomic studies that traditionally investigate this subject.

Extended length of stay and related costs associated with dementia in acute care hospitals in Ireland

OBJECTIVE

To estimate the additional impact of dementia on in-patient length of stay (LOS) and related costs in Irish acute hospitals. Both principal and secondary diagnosis effects are estimated and valued.

METHODS

This is a cross-sectional study based on administrative data collected on all public hospital in-patient discharges in Ireland for people aged 65 years and older in 2019. Coarsened exact matching (CEM) was undertaken to account for observed confounders between dementia and non-dementia groups, while generalised linear modelling (GLM) was used to compare differences in LOS.

RESULTS

Patients with a principal diagnosis of dementia spent on average 17.5 (CI: 15.42, 19.56; p < .01) d longer in hospital than similar patients with no principal diagnosis of dementia. LOS was 6.7 (CI: 6.31, 7.14; p < .01) d longer for patients with a secondary diagnosis of dementia compared to similar patients with no secondary diagnosis of dementia. The additional annual cost of care for patients in hospitals with a secondary (principal) diagnosis of dementia was €62.0 million (€13.2 million).

CONCLUSIONS

This study highlights the economic impact of extended LOS for patients with dementia in Irish acute hospitals. Addressing specific dementia-related needs of people in hospital is likely to optimise resource use and decrease health care costs in acute care settings.

The ‘Red Herring’ Hypothesis: Some Theory and New Evidence

The ‘red herring’ hypothesis (RHH) claims that apart from income and medical technology, proximity to death rather than age constitutes the main determinant of healthcare expenditure (HCE). This paper seeks to underpin the RHH with some theory to derive new predictions also for a rationed setting, and to test them against published empirical evidence. One set comprising ten predictions uses women’s longer life expectancy as an indicator of the difference in time to death in their favor. Out of 28 testing opportunities drawn from the published evidence, in the case of no rationing seven out of eleven result in full and two in partial confirmation; in the case of rationing, twelve out of 17 result in full and one in partial confirmation. The other set, containing 35 testing opportunities, concerns the age profile of HCE. In the case of no rationing, seven out of twelve result in full and four in partial confirmation; in the case of rationing, eleven out of 23 in full and nine in partial confirmation. There are but ten contradictions in total. Overall, the new tests of the RHH can be said to receive a good deal of empirical support, both from countries and settings with and without rationing.

Proportion of deaths in hospital in European countries: trends and associations from panel data (2005-2017)

BACKGROUND

End-of-life care attracts major policy interest. Place of death is an important metric of individual experience and health system performance. Most people prefer to die at home, but hospital is the most common place of death in high-income countries. Little is known about international trends in place of death over time.

METHODS

We aimed to collate population-level data on place of death in Europe from 2005 to 2017, and to evaluate association with national characteristics and policy choices. We sought data on hospital as the place of death from the 32 European Economic Area countries. We identified national economic, societal, demographic and health system predictors from Eurostat, OECD and the WHO. We analyzed these cross-national panel data using linear regression with panel-corrected standard errors.

RESULTS

Our analytic dataset included 30 countries accounting for over 95% of Europe's population. Average national proportion of deaths occurring in hospital in the study period ranged from 26% to 68%, with a median of 52%. Trends vary markedly by region and wealth, with low and decreasing rate in the North-West, and high and increasing prevalence in the South and East. Controlling for demographic and economic factors, strong palliative care provision and generous government finance of long-term care were associated with fewer hospital deaths.

CONCLUSIONS

We found modifiable policy choices associated with hospital mortality, as well as wider structural economic and societal factors. Policymakers can act to reduce the proportion of dying in hospital.

Using predicted length of stay to define treatment and model costs in hospitalized adults with serious illness: an evaluation of palliative care

BACKGROUND

Economic research on hospital palliative care faces major challenges. Observational studies using routine data encounter difficulties because treatment timing is not under investigator control and unobserved patient complexity is endemic. An individual's predicted LOS at admission offers potential advantages in this context.

METHODS

We conducted a retrospective cohort study on adults admitted to a large cancer center in the United States between 2009 and 2015. We defined a derivation sample to estimate predicted LOS using baseline factors (N = 16,425) and an analytic sample for our primary analyses (N = 2674) based on diagnosis of a terminal illness and high risk of hospital mortality. We modelled our treatment variable according to the timing of first palliative care interaction as a function of predicted LOS, and we employed predicted LOS as an additional covariate in regression as a proxy for complexity alongside diagnosis and comorbidity index. We evaluated models based on predictive accuracy in and out of sample, on Akaike and Bayesian Information Criteria, and precision of treatment effect estimate.

RESULTS

Our approach using an additional covariate yielded major improvement in model accuracy: R² increased from 0.14 to 0.23, and model performance also improved on predictive accuracy and information criteria. Treatment effect estimates and conclusions were unaffected. Our approach with respect to treatment variable yielded no substantial improvements in model performance, but post hoc analyses show an association between treatment effect estimate and estimated LOS at baseline.

CONCLUSION

Allocation of scarce palliative care capacity and value-based reimbursement models should take into consideration when and for whom the intervention has the largest impact on treatment choices. An individual's predicted LOS at baseline is useful in this context for accurately predicting costs, and potentially has further benefits in modelling treatment effects.

[Healthcare expenditure and the impact of age: a detailed analysis for survivors and decedents]

BACKGROUND

Germany faces various socio-political challenges due to its ongoing ageing population. Significant increases in social security contributions are widely expected. The impact of ageing on healthcare expenditure is a controversial issue. Experts agree that costs for end-of-life care account for a significant part of total healthcare expenditures. For a meaningful forecast, detailed information on healthcare costs differentiated by survivors and decedents is necessary. Extensive data are hardly available for Germany. The aim of the analysis was therefore to describe healthcare costs in the statutory health insurance.

METHODS

The basis for the calculation is billing data from the statutory health insurance "AOK Niedersachsen" (Lower Saxony). Persons who survived or died in 2017 were included in the analysis. Average costs were standardised.

RESULTS

The data of 2.46 million survivors and 34,307 decedents were analysed. The average annual healthcare costs were 2756 € for survivors and 21,830 € for decedents in the last year of life. The average healthcare costs for survivors increase with age whereas costs for decedents are highest in younger age groups and decline with increasing age. A detailed analysis of end-of-life costs shows an exponential increase of costs in the last three years of life with the highest costs in the quarter before death (10,577 €).

DISCUSSION

The analysis gives a detailed overview on the structure of healthcare expenditure in the statutory health insurance and can serve as a basis for future forecasts regarding healthcare expenditure.

ICU-Mortality in Old and Very Old Patients Suffering From Sepsis and Septic Shock

Purpose: Old (>64 years) and very old (>79 years) intensive care patients with sepsis have a high mortality. In the very old, the value of critical care has been questioned. We aimed to compare the mortality, rates of organ support, and the length of stay in old vs. very old patients with sepsis and septic shock in intensive care.

Methods: This analysis included 9,385 patients, from the multi-center eICU Collaborative Research Database, with sepsis; 6184 were old (aged 65–79 years), and 3,201 were very old patients (aged 80 years and older). A multi-level logistic regression analysis was used to fit three sequential regression models for the binary primary outcome of ICU mortality. A sensitivity analysis in septic shock patients (n = 1054) was also conducted.

Results: In the very old patients, the median length of stay was shorter (50 ± 67 vs. 56 ± 72 h; p < 0.001), and the rate of a prolonged ICU stay was lower (>168 h; 9 vs. 12%; p < 0.001) than the old patients. The mortality from sepsis was higher in very old patients (13 vs. 11%; p = 0.005), and after multi-variable adjustment being very old was associated with higher odds for ICU mortality (aOR 1.32, 95% CI 1.09–1.59; p = 0.004). In patients with septic shock, mortality was also higher in the very old patients (38 vs. 36%; aOR 1.50, 95% CI 1.10–2.06; p = 0.01).

Conclusion: Very old ICU-patients suffer from a slightly higher ICU mortality compared with old ICU-patients. However, despite the statistically significant differences in mortality, the clinical relevance of such minor differences seems to be negligible.

Healing, surviving, or dying? - projecting the German future disease burden using a Markov illness-death model

BACKGROUND

In view of the upcoming demographic transition, there is still no clear evidence on how increasing life expectancy will affect future disease burden, especially regarding specific diseases. In our study, we project the future development of Germany's ten most common non-infectious diseases (arthrosis, coronary heart disease, pulmonary, bronchial and tracheal cancer, chronic obstructive pulmonary disease, cerebrovascular diseases, dementia, depression, diabetes, dorsal pain and heart failure) in a Markov illness-death model with recovery until 2060.

METHODS

The disease-specific input data stem from a consistent data set of a major sickness fund covering about four million people, the demographic components from official population statistics. Using six different scenarios concerning an expansion and a compression of morbidity as well as increasing recovery and effective prevention, we can show the possible future range of disease burden and, by disentangling the effects, reveal the significant differences between the various diseases in interaction with the demographic components.

RESULTS

Our results indicate that, although strongly age-related diseases like dementia or heart failure show the highest relative increase rates, diseases of the musculoskeletal system, such as dorsal pain and arthrosis, still will be responsible for the majority of the German population's future disease burden in 2060, with about 25-27 and 13-15 million patients, respectively. Most importantly, for almost all considered diseases a significant increase in burden of disease can be expected even in case of a compression of morbidity.

CONCLUSION

A massive case-load is emerging on the German health care system, which can only be alleviated by more effective prevention. Immediate action by policy makers and health care managers is needed, as otherwise the prevalence of widespread diseases will become unsustainable from a capacity point-of-view.